• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.31-38
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• 2005

This paper proposes an object-based image retrieval scheme using color adjacency and clustering method. Color adjacency features in boundary regions are utilized to extract candidate blocks of interest from image database and a clustering method is used to extract the regions of interest(ROI) from candidate blocks of interest. To measure the similarity between the query and database images, the histogram intersection technique is used. The color pair information used in the proposed method is robust against translation, rotation, and scaling. Consequently, experimental results have shown that the proposed scheme is superior to existing methods in terms of ANMRR.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.517-519
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• 2001

클래스 라이브러리, 설계 패턴, 프레임워크 등의 재사용 기술과 더불어 근래 들어 소프트웨어 컴포넌트 기술이 크게 각광을 받았다. 산업계에서도 Microsoft사 중심의 COM+와 Sun사 중심의 Enterprise Java Bean (EJB) [1]이 대두되 있으며 있따른 제품들이 출시되 있다. 소프트웨어의 재사용 단위가 객체에서 컴포넌트로 이동함으로써 기존 객체 중심의 개발 방법론, 모델링 및 개발도구들이 컴포넌트 개념을 포함하며 발전하 있다. 본 논문은 컴포넌트 추출에 초점을 두 있다. 서블릿[2] 프로그램에서 EJB 컴포넌트 추출을 위한 기법을 제공한다. 서블릿기반으로 개발된 웹 프로그램을 분석하여 재사용 가능한 EJB 컴포넌트를 추출하여 차후 유사만 어플리케이션 개발 시 활용하고자 한다. 서블릿의 메소드들을 분석하여 메소드 특성에 따라 session bean [1] 또는 entity bean [11의 메소드로 변환한다. 제안된 컴포넌트 추출 과정을 기술하 Unified Modeling Language(UML)[3] 기반의 추출 모듈에 대한 분석, 설계 다이어그램을 제공한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.751-754
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• 2005

본 논문에서는 인간의 머리부분을 흉내 낸 시각 시스템으로서, 4 축의 각도 조절이 자유로운 시스템에 두 개의 CCD 카메라를 연결하여 실시간으로 입력되는 영상 데이터로부터 레이져 포인터의 위치 정보를 추출한 후 주 카메라를 이용하여 시스템 전체를 레이저 포인터의 중심위치로 이동한 후 버전스 각도(vergence angle)를 이용하여 실시간으로 오브젝트의 절대거리를 측정하는 효과적인 시스템을 제안하였다. 객체까지의 거리는 교차식 카메라를 적용한 스테레오 비전 시스템을 사용하여 삼각측량의 방법으로 거리를 측정하였다. 실험결과 객체에 대한 거리 측정 오차가 평균 2% 나타남으로써 제안한 알고리즘을 이용한 이동객체의 거리측정 가능성을 제시하였다.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.52-58
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• 2007

In this paper we propose a new robust method to extract accurate human silhouettes indoors with active stereo camera. A prime application is for gesture recognition of mobile robots. The segmentation of distant moving objects includes many problems such as low resolution, shadows, poor stereo matching information and instabilities of the object and background color distributions. There are many object segmentation methods based on color or stereo information but they alone are prone to failure. Here efficient color, stereo and image segmentation methods are fused to infer object and background areas of high confidence. Then the inferred areas are incorporated in graph cut to make human silhouette extraction robust and accurate. Some experimental results are presented with image sequences taken using pan-tilt stereo camera. Our proposed algorithms are evaluated with respect to ground truth data and proved to outperform some methods based on either color/stereo or color/contrast alone.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.271-277
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• 2017

In the image processing, foreground image extraction is mainly applied to recognize a moving object or an object. In the game, the objects included in the foreground image can be mainly characters, non player characters, items, and the like. These objects can be the player's primary concern with objects that are the target of players' movement, attack, defense, and collection. In this background, this research is a study to extract players' interest areas. To this end, first, the foreground image is extracted. Second, the extracted foreground image is accumulated for a certain period of time, and the image is displayed as a result image. The accumulated foreground image according to the play time helps to know the location and frequency of screen appearance of game objects. This study can help players design their interest areas and design an efficient UX/UI.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.917-927
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• 2020

The Ministry of Land, Infrastructure and Transport of Korea is developing a CAS 500-1/2 satellite capable of photographing a GSD 0.5 m level image, and is developing a technology to utilize this. Therefore, this study attempted to develop a geospatial feature extraction technique aimed at automation as a technique for utilizing CAS 500-1/2 satellite images. KOMPSAT-3A satellite images that are expected to be most similar to CAS 500-1/2 were used for research and the possibility of automation of geospatial feature extraction was analyzed through relative radiometric normalization. For this purpose, the parameters and thresholds were applied equally to the reference images and relative radiometric normalized images, and the geospatial feature were extracted. The qualitative analysis was conducted on whether the extracted geospatial feature is extracted in a similar form from the reference image and relative radiometric normalized image. It was also intended to analyze the possibility of automation of geospatial feature extraction by quantitative analysis of whether the classification accuracy satisfies the target accuracy of 90% or more set in this study. As a result, it was confirmed that shape of geospatial feature extracted from reference image and relative radiometric normalized image were similar, and the classification accuracy analysis results showed that both satisfies the target accuracy of 90% or more. Therefore, it is believed that automation will be possible when extracting spatial objects through relative radiometric normalization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1843-1850
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• 2004

If the location information of a great number of cars kept for business with telematics terminals is acquired and managed efficiently, this information forms the foundation for controlling cars and traffic flows. The studies on the pure spatial indices have focused on the efficient retrievals. However, the acquisition and management of the terminal location of moving objects are more important than the efficiency of the query processing in the moving object databases. Therefore, it will be need to adopt parallel processing system for the moving object databases which should maintain the object's current location as precise as possible. This paper proposes a location management system using CDMA communications of telematics terminals. More precisely, we propose a architecture of spatial indexing mobile objects using multiple processors, and also newly propose a method of splitting buckets using the properties of moving objects in order to minimize the number of database updates. We also propose a acquisition method for gathering the location information of moving objects and passing the information of the bucket extents in order to reduce the amount of passed messages between processors.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.1-8
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• 2003

This paper proposes an object-based image retrieval technique based on the dominant color pair information. Most of existing methods for content based retrieval extract the features from an image as a whole, instead of an object of interest. As a result, the retrieval performance tends to degrade due to the background colors. This paper proposes an object based retrieval scheme, in which an object of interest is used as a query and the similarity is measured on candidate regions of DB images where the object may exist. From the segmented image, the dominant color pair information between adjacent regions is used for selecting candidate regions. The similarity between the query image and DB image is measured by using the color correlogram technique. The dominant color pair information is robust against translation, rotation, and scaling. Experimental results show that the performance of the proposed method has been improved by reducing the errors caused by background colors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1652-1659
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• 2004

In this paper, we propose the algorithm that automatically measures the height of the object to move on the base plane by using the geometric information. To extract a moving object from real-time images creates the background image and each pixel is modeled by the three values. The extracted region is represented by cardboard model and calculates the coordinate center in the each part. The top and bottom point of an object are extracted by the calculated coordinate center and an iterative computation. The two points, top and bottom, are used for measuring the height. Given the vanishing line of the ground plane, the vertical vanishing point, and at least one reference height in the scene; then the height of any point from the ground may be computed by specifying the image of the point and the image of the vertical intersection with the ground plane at that point. Through a confidence valuation of the height to be measured, we confirmed similar actual height and result in the simulation experiment.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.13-18
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• 2007

효과적인 이미지 검색을 위하여, 이미지의 저수준 시각 정보로부터 고수준 의미 정보를 추출하는 기술에 관한 많은 연구가 이루어지고 있다. 특히 최근에는 Support Vector Machine과 같은 기계 학습 기법을 이용한 이미지 어노테이션 시스템의 개발이 활발히 진행중이이다. 그러나 기존의 연구들은 단편적인 이미지 정보만을 추출함에도 불구하고, 그 성능이 여전히 만족스럽지 못하다. 본 논문에서는 Support Vector Machine과 온톨로지를 이용하여 이미지의 다양한 정보를 효과적으로 추출 및 기술할 수 있는 시스템을 제안한다. 특히 온톨로지는 특정 도메인의 상세한 지식 표현과 추론을 위한 지식베이스로서, 본 논문에서는 Support Vector Machine을 이용하여 이미지 안에 존재하는 객체들의 컨셉을 판별하고 이미지 어노테이션 온톨로지와 생태계 온톨로지를 이용하여 공간 관계, 천적 관계와 같은 객체간 의미 관계를 자동적 자동적으로 추출하는 방법을 제안한다.